Advanced Sample Surveys

Paper Code: 
STT423(B)
Credits: 
5
Contact Hours: 
75.00
Max. Marks: 
100.00
Objective: 

This is an advanced course in Sampling Techniques that aims at describing some advanced level topics for students who wish to pursue research in Sampling Techniques. This course prepares students for undertaking research in this area. This also helps prepare students for applications of this important subject to Statistical System in the country.

Course

Learning outcomes (at course level

Learning and teaching strategies

Assessment Strategies

 

Paper Code

Paper Title

STT423(B)

Advanced Sample Surveys

(Theory)

The students will be able to –

 

CO105: Understand the principles underlying sampling as a means of making inferences about a population,

CO106: Understand the concepts of bias and sampling variability and strategies for reducing these biases.

CO107: Be able to analyse data from multi-stage surveys,

CO108: Have an appreciation of the practical issues arising in sampling studies.

Approach in teaching:

Interactive Lectures,

Group Discussion,

Classroom Assignment

Problem Solving Sessions

 

Learning activities for the students:

Assignments

Seminar

Presentation

Subject based  Activities

Classroom Quiz

Assignments

Class Test

Individual Presentation

 

15.00

Varying probabilities and without replacement. Des Raj ordered estimates, Murthy’s unordered estimates (general cases), estimation of linear classes of estimates, Narain-Horvitz-Thompson’s estimator and variance. Inclusion probabilities(n=2).

 

 

15.00

Estimation of variance of Horvitz-Thompson estimator, Horvitz-Thompson, Yates-Grundy, Sen-Midzuno’s results, Midzuno Sampling scheme. Rao-Hartley-Cochran sampling scheme.

 

 

15.00

Brewer’s sampling design, Durbin’s grouped and ungrouped procedure, systematic sampling with varying probabilities, multivariate extensions of ratio and regression estimates.

 

15.00

Sub sampling using varying probabilities with and without replacement: unbiased estimator, its variance and estimates of the variance, Durbin’s result.

 

 

15.00

Double sampling in regression estimation, successive sampling for h ≥ 2 ocassions. Super population concepts and super population models (introduction). Optimal properties of ratio and regression method of estimation.

 

Essential Readings: 
  • Cocharan,W.G.(1997): Sampling Techniques III ed, John Wiley Pub. New Yark.
  • Des Raj and Chandok (1999): Sampling Theory , Norsa Pub. New Delhi.
  • Murthy, M.N. (1967) : Sampling Theory and Methods, Statistical Pub.Society, Kolkata.
  • Chaudhary, A and. Mukherjee R (1988): Randomised Response: Theory & Techniques, Marcel Dekker Inc New Yark.
  • Shukhatme, P.V.et al(1984): Sampling Theory of Surveys in the Applications, Iawa State press & Ind.Soc. of Agri. Stat.
  • Mukhopadhya, P. (1996): Inferencial Problems in Survey Sampling, New Age Intenational.
  • Singh, D. & Choudhary,F.S.(2002): Theory and Analysis of Sample Surveys and its Applications, New Age international Publication.

 

Academic Year: